(Senior) Machine Learning Engineer / Data Scientist

About ProFound Therapeutics

ProFound Therapeutics is pioneering the discovery of the expanded human proteome to unlock a new universe of potential therapeutics. By integrating multi-omics, advanced computation, and translational biology, we aim to reveal and characterize thousands of previously uncharted proteins and systematically explore their role in health and disease.

The Role

We are seeking a highly motivated Senior Machine Learning Engineer / Data Scientist to join our AI/ML team. This individual will play a central role in designing and implementing advanced AI/ML systems with a focus on Retrieval-Augmented Generation (RAG), graph-based RAG, large language models (LLMs), agentic orchestration, and conversational AI (chatbot) solutions. Working closely with the Head of AI/ML and cross-functional partners, you will build and optimize LLM-powered pipelines and multi-agent systems that integrate knowledge graphs, multi-omics data, and biological context to uncover disease-driving proteins and pathways. The insights generated will directly support therapeutic discovery and development.

Key Responsibilities

• Architect and implement scalable RAG and LLM-based systems that integrate multi-modal data sources, including knowledge graphs, documents, and structured biological datasets.
• Design and deploy RAG and graph-based RAG pipelines that leverage LLMs and knowledge graphs to retrieve, reason over, and synthesize complex biological information.
• Build and maintain agentic orchestration frameworks (multi-agent systems) that coordinate LLM-based agents for end-to-end scientific reasoning, data retrieval, and decision support.
• Collaborate with data engineering teams to design data pipelines that harmonize and prepare large-scale omics datasets for model training.
• Develop and optimize conversational AI (chatbot) interfaces that enable scientists and stakeholders to query, explore, and interact with internal data and model outputs using natural language.
• Partner with experimental scientists to ensure model outputs are biologically interpretable and experimentally testable.
• Stay abreast of advances in LLMs, RAG architectures, agentic AI, and conversational AI; bring innovative ideas into the team.

Qualifications

• Ph.D. in Computer Science, Machine Learning, Applied Mathematics, Computational Biology, or related field with 1–3 years of industry experience (preferred); or M.S. in a related field with 4–6 years of industry experience.
• Proven track record in building LLM-based applications, with hands-on expertise in RAG, graph-based RAG, agentic orchestration, and/or chatbot development.
• Proficiency in Python and LLM/ML frameworks such as LangChain, Hugging Face Transformers, PyTorch, or similar.
• Experience working with multi-omics or high-dimensional biological data is a plus but not required.
• Familiarity with probabilistic modeling, causal reasoning, or statistical inference is a plus.
• Strong experience with knowledge graph technologies, graph databases, and vector databases.
• Demonstrated ability to work in cross-disciplinary teams, communicate complex ideas clearly, and deliver results in fast-moving environments.

 

Why Join Us?

This role offers a unique opportunity to shape a next-generation AI/ML platform at the intersection of computation and drug discovery. You will work in a collaborative environment with leaders in biology, computation, and therapeutics — helping to expand the boundaries of the proteome and accelerate the development of new medicines for patients.

ABOUT FLAGSHIP PIONEERING:

Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies have addressed humanity’s most urgent challenges: vaccinating billions of people aga